Classification of Chinese Famous Tea Base on Visible and Near Infrared Hyperspectra Imaging

Abstract

A total of 180 samples from six varieties of typical tea (30 for each variety) were collected for hyperspectral image classification. The first 2 principal components (PCs) explained over 97% of variances of all spectral information. Gray-level co-occurrence matrix (GLCM) analysis was implemented on the 2 principal component (PC) images to extract 24… (More)

6 Figures and Tables

Topics

  • Presentations referencing similar topics